What we do

Absolute Return

Our two flagship investment programs were launched in 1991 and 2003 respectively. They are multi award winning and have the objective of achieving consistent returns, in variable market conditions with a risk profile that is less volatile than market indices. The performance of these programs, which is decorrelated from market indices, represents our Alpha strategies.

These programs are the zenith of our collective capability and are structured to reflect the fact that achieving a combination of acceptable risk and decorrelation from market indices requires considerable expertise, investment and R&D capability. The strategies in the programs are therefore subject to constant evolution in order to maintain the Alpha characteristics and manage decay.

Many of the strategies are based on exploiting medium term (days to months) inefficiencies in markets and so portfolio turnover is relatively high.

Alternative Beta

For over 20 years we have invested in quantitative research and development resulting in the creation of successful absolute return programs. A decorrelated strategy, Alpha, is by definition capacity constrained, complex and has associated high fees making it attractive to only a small minority of investors. Mainstream investor appetite for simpler strategies with an attractive fee structure is growing. Mindful of this and the constraints of the absolute return programs, in 2012 we began developing a different type of program, which would use the firm’s existing expertise and capital expenditure to appeal to a broader set of investors. The programs were launched in 2013 and 2014 with the hallmarks of our quantitative approach but with less complexity, some correlation and appropriate fees.

Alternative Beta, a definition: ‘Alternative strategies’ have historically been associated with hedge funds on account of the fact that the traded instruments in such strategies are often not ‘traditional’ equities and bonds and the returns profile is often decorrelated from equity and bond benchmarks. Such strategies have now made their way into more mainstream investment circles, but the investment styles continue to be known as ’alternative’. Alternative Beta is therefore an investment style with returns correlated to these now well-known alternative benchmarks and therefore not to traditional equity or bond benchmarks such as the S&P 500. The definition of the alternative benchmark is not as clear cut, or accessible, as in the case of equity or bond indices, but is instead assumed to be a standard implementation of a standard alternative strategy.

While a strict definition of Alternative Beta strategies remains elusive, various important themes tend to emerge:

Strategies that persist over long periods of time – often decades or even centuries. Levels of statistical significance need to be sufficiently high to establish strong conviction that the systems are not over-fitted but well anchored in the structure of the markets.

Strategies that are slower moving, as opposed to the short term inefficiencies that are generally arbitraged away through time and exploited in an absolute return strategy. Importantly the slower strategies tend to be scalable to higher capacity.

Strategies that are explainable, understandable and plausible.

Alternative beta strategies can generally be split into two types – risk rewarding or so called risk premia and pure market anomalies often of behavioural origin.

In short, a diversified Alternative Beta program is a mix of simple, well-justified strategies, seeking to deliver persistent excess returns with scalable capacity, while exhibiting low correlation to traditional equity and fixed income benchmarks.

CFM Product Showcase from Financial Standard

Implementation

The synergies between the Alternative Beta and our Absolute Return programs make for a highly differentiated approach when it comes to implementing the Alternative Beta strategies and one that shouldn’t be underestimated. This differentiation manifests itself in the following ways:

Portfolio Construction: portfolio construction, together with return generation and execution, is a vital aspect of building a sound investment program. It requires robust data and developed statistical methods which we have honed over many years.

Systematic risk management based on in-house IT infrastructure: our IT/Data infrastructure, built over two decades at a cost of more than €100m, has been specifically designed for quasi real time risk evaluation. So while the trading patterns are slower in the Alternative Beta strategy, regular updates of positions and market condition indicators are important in building a reliable risk control infrastructure.

Robust operational risk control: the monitoring and management of operational risk at all levels in the production chain is important. While operational risk monitoring tools are embedded in the trading systems and maintained by the front office teams, we also maintain a dedicated, independent risk team, reporting directly to our firm’s directors, whose mandate is to independently validate financial risk estimates and to independently impose operational risk limits.

Industrialized, large-scale data processing: our data team, comprised of approximately 20 IT engineers, is responsible for collecting, cleaning, manipulating, and managing terabytes of incoming data every day. Our data sets range from price-related information (e.g., prices, implied volatilities) to fundamentals (e.g., corporate financial statements) and non-financial information for trading ideas that exploit idiosyncratic, market-specific inefficiencies. Given the lower turnover of Alternative Beta strategies, achieving statistical significance is facilitated by the longest back tests possible. Time-series data for futures and equities extends back at least to the 1960s and 1970s and, where possible, we also maintain certain data series as far back as 1800 (e.g., monthly data for many indices, commodities, bonds, and various interest rates). We currently monitor approximately one million instruments.

The Importance of minimizing costs: controlling trading costs in the implementation of any strategy is critical. Our dedicated execution research team manages our infrastructure and seeks to model, measure and reduce costs. We have an extensive database of the execution of our own trades, data which is not commercially available, and which provides valuable insight into the dynamics of price impact. Our execution team has also published numerous papers in this field, in particular on the subject of market impact.